Measuring the efficiency and productivity changes in international airports before and during the COVID-19 pandemic

Shih-Pin Chen and Chun-Shao Chen

Transport Policy, 2025, vol. 167, issue C, 78-90

Abstract: In today's globalized environment, the aviation industry is a critical economic pillar that influences trade, tourism, and national economies. Accounting for the COVID-19 pandemic and the US‒China trade war, this study uses data envelopment analysis (DEA) with an assurance region (AR) to measure the efficiency of 19 international airports from 2017 to 2021 and applies the Malmquist productivity index (MPI) to analyze productivity changes. Airport selection is based on Skytrax rankings, with inputs including runway length, terminal area, and operational expenses, and outputs including the number of passengers, cargo volume, and total revenue. Key findings indicate that the Seoul Incheon (ICN), Hong Kong (HKG), London Heathrow (LHR), Taiwan Taoyuan (TPE), and Jakarta (CGK) airports were efficient, suggesting disparities with the Skytrax rankings. The MPI decreased by 16% across the 19 airports over the study period, with volatility and a notable decline. Noteworthy progress has occurred at the Copenhagen (CPH), HKG, CGK, and Rome Fiumicino (FCO) airports. The geometric mean of the MPI for 2020–2021 decreased to 0.514, indicating that COVID-19 had a significant impact on airport productivity, with technological advancements driving productivity shifts. Furthermore, a management decision matrix classified the 19 airports into seven categories based on their relative aggregate efficiency (AE) and efficiency change (EC) scores, with HKG, CGK, and ICN demonstrating high competitiveness and rapid progress; strategies for improving or maintaining a competitive advantage in each category are presented. The findings of this paper can help airport managers understand relative efficiency and improvement directions, serving as a reference for future strategies.

Keywords: Data envelopment analysis; Malmquist productivity index; Efficiency; Management matrix analysis; Efficiency change (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.tranpol.2025.02.023

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